Pathology data capture

ABSTRACT

A method for pathology data capture includes magnifying a pathology sample with a microscope to form magnified pathology images, and recording the magnified pathology images with a digital camera. The method further includes transferring the magnified pathology images to a processing apparatus, where the processing apparatus performs operations including: stitching together the magnified pathology images to form a plurality of high-resolution images, where the plurality of high-resolution images include un-imaged holes; and generating image data that is not actual image data for the un-imaged holes.

CROSS-REFERENCE TO RELATED APPLICATIONS

This application is a continuation of U.S. patent application Ser. No.15/225,247, filed on Aug. 1, 2016, the contents of which are hereinincorporated by reference.

TECHNICAL FIELD

This disclosure relates generally to systems/methods for aiding inpathology.

BACKGROUND INFORMATION

Pathology is a medical discipline related to the study and diagnosis ofdisease. Most frequently pathology involves the analysis and examinationof body-fluid, tissue, and cell samples. As a field of general study andresearch, pathology relates to four aspects of disease: (1) etiology,(2) pathogenesis, (3) morphologic changes, and (4) consequence ofmorphologic changes.

The field of pathology dates back to antiquity. Many early societiespossessed a rudimentary understanding of biological conditions as aresult of dissection/examination. By the Hellenic period of Greece, acausal study of disease had emerged in human culture. Humanunderstanding of disease through pathology continued to advancepiecemeal as time progressed; for instance many advances in pathologyare attributable to the medieval era of Islam.

However, modern pathology only emerged as a distinct field of study inthe late 1800's with the advent of microbiology. Now pathology is amajor medical practice that is divided into a number of subdisciplines.In all of these subdisciplines, collaboration between multiple doctorsmay be important to ensure accurate diagnosis. Furthermore, trainingpathologists requires the trainee to examine a huge number of samples inorder for the trainee to become familiar with the many possible variantsof disease.

BRIEF DESCRIPTION OF THE DRAWINGS

Non-limiting and non-exhaustive embodiments of the invention aredescribed with reference to the following figures, wherein likereference numerals refer to like parts throughout the various viewsunless otherwise specified. The drawings are not necessarily to scale,emphasis instead being placed upon illustrating the principles beingdescribed.

FIG. 1 illustrates a system for pathology data capture, in accordancewith an embodiment of the disclosure.

FIG. 2 illustrates a pathology database, in accordance with anembodiment of the disclosure.

FIG. 3 illustrates image entries in the pathology database of FIG. 2, inaccordance with an embodiment of the disclosure.

FIG. 4 is a flow chart illustrating a method of pathology data capture,in accordance with several embodiments of the disclosure.

DETAILED DESCRIPTION

Embodiments of an apparatus and method for pathology data capture aredescribed herein. In the following description numerous specific detailsare set forth to provide a thorough understanding of the embodiments.One skilled in the relevant art will recognize, however, that thetechniques described herein can be practiced without one or more of thespecific details, or with other methods, components, materials, etc. Inother instances, well-known structures, materials, or operations are notshown or described in detail to avoid obscuring certain aspects.

Reference throughout this specification to “one embodiment” or “anembodiment” means that a particular feature, structure, orcharacteristic described in connection with the embodiment is includedin at least one embodiment of the present invention. Thus, theappearances of the phrases “in one embodiment” or “in an embodiment” invarious places throughout this specification are not necessarily allreferring to the same embodiment. Furthermore, the particular features,structures, or characteristics may be combined in any suitable manner inone or more embodiments.

The instant disclosure improves pathology data capture by cheaplyintegrating slide digitization into the pathologist's workflow(non-disruptively). In modern pathology, sometimes pathology samples arescanned at high-resolution to create a digital database. Depending onthe complexity of the scan this may take a long time and result in ahuge amount of data being collected. Furthermore large portions of thesample may be irrelevant to diagnosis or training (e.g., if a sample isseveral centimeters large and the diseased cells are only in a 1 mmarea, digitizing the whole sample is a waste of memory). Accordingly, byonly recording the magnified images/video that a trained pathologistchooses to examine, in conjunction with the pathologists vocalannotations, a database that only contains information germane to thediagnosis/identification of disease is created.

FIG. 1 illustrates a system 100 for pathology data capture, inaccordance with an embodiment of the disclosure. System 100 includes:microscope 101, digital camera 103, microphone 105, controller 107,processing apparatus 109, network 111, and storage 121. System 100provides for the continuous recording of what the pathologist sees,performs automatic mosaicking of the resulting high-resolution images,captures slide displacement, and annotates the reconstructed mosaickedimage with diagnostic information provided by the pathologist.

Microscope 101 houses digital camera 103, and digital camera 103 isoptically coupled to microscope 101 to continuously capture magnifiedpathology images produced by microscope 101. In some embodiments,digital camera 103 may not be housed in microscope 101 and may be anadd-on. However, one skilled in the art will appreciate that digitalcamera 103 may be coupled to microscope 101 in a number of ways, inaccordance with the teachings of the present disclosure. It is worthnoting that microscope 101 has many different magnification settings,all of which can be recorded by digital camera 103. Additionally,microphone 105 is coupled to receive voice annotation of auser/pathologist.

Processing apparatus 109 (i.e., a desktop computer) is electricallycoupled to digital camera 103 to receive the magnified pathology imagesand electrically coupled to microphone 105 to receive the voiceannotation from the pathologist (i.e., the cartoon person). It is worthnoting that all devices in system 100 may communicate wirelessly in someembodiments. Processing apparatus 109 includes logic that when executedby processing apparatus 109 causes processing apparatus 109 to performoperations including: recording the magnified pathology images and thevoice annotation to a storage medium (e.g., hard drive, RAM, ROM, flashmemory, etc.), and indexing the magnified pathology images and the voiceannotation with respect to recording time. Although a desktop computeris depicted as processing apparatus 109, other computing devices can beused as processing apparatus 109. For example tablets, phones, laptops,remote servers, processors/microcontrollers incorporated in microscope101, etc. can all function as processing apparatus 109.

In the depicted embodiment, the magnified pathology images and the voiceannotation form a database, and the database may be uploaded to remoteor local servers via network 111. As shown processing apparatus 109 maybe both electrically coupled to network 111 and storage 121. In otherembodiments, processing apparatus 109 may also exist on remote serversin the cloud, or processing apparatus 109 may be distributed across manydevices/systems. However, as depicted, processing apparatus 109 may alsoexist locally.

Microscope 101 has a stage including first mechanical to electricaltransducers 113 to track a position of the stage. The position of thestage may be sent from the first mechanical to electrical transducers113 to the processing apparatus 109. Similarly, second mechanical toelectrical transducers 115 are coupled to microscope 101 to measure themagnification setting of microscope 101. The magnification setting maybe sent from the second mechanical to electrical transducers 115 toprocessing apparatus 109. However, in another or the same embodiment,the magnification setting may be captured through an external videocamera.

As illustrated controller 107 is coupled to processing apparatus 109.Controller 107 may be used to control image/video capture of digitalcamera 103, record voice annotations from microphone 105, adjust theposition of the microscope stage, and adjust illumination settings ofmicroscope 101 (e.g., make illuminator brighter/darker, polarized,top-illuminated, bottom-illuminated, etc.). Although in the depictedembodiment controller 107 is wired to processing apparatus 109, in otherembodiments controller 107 may communicate with processing apparatus 109wirelessly. In some embodiments, controller 107 may be a virtualcontroller running on processing apparatus 109, and may receive vocalinstructions through microphone 105, or a kinetic instructions via amouse/keyboard connected to the processing apparatus 109. In oneembodiment the user may state commands to microphone 105, and avirtual/embedded controller in processing apparatus 109 executes theinstructions. For example, the user may say “OK microscope, turn onmicroscope lighting and start visual and audio recording”, “pause audiorecording”, “pause visual recording”, “move the microscope stage oneframe to the left”, “change to linearly polarized light”, etc. In theseand other embodiments, microphone 105 can be integrated into digitalcamera 103 and/or microscope 101, or it can be a separate device.Microphone 105 can start recording synchronously with digital camera 103or it can be manually or automatically turned on when digital camera 103is on. Alternatively, microphone 105 can passively listen for keywordsbefore starting recording (e.g., “OK Microscope”).

Digital camera 103 can be either continuously on or it can be turned onby the pathologist when a new slide is examined. Digital camera 103 canalso be motion triggered (i.e., it starts recording when the slidestarts moving and/or the zoom or focus level of microscope 101 ischanged). Alternatively, a presence sensor (optical or otherwise) can beadded to the eyepiece of microscope 101, and digital camera 103 isautomatically turned on when the presence of the pathologist lookingthrough microscope 101 is detected.

Microscope 101 may come with, or be outfitted to include, gaze detectionhardware and software (depicted as the two dashed lines from theeyepiece of microscope 101 to the user's eyes). Accordingly, system 100may track the gaze of the user to determine a region of interest (e.g.,cancer cells in an image); the region of interest may be indexed withrespect to recording time, magnification setting, and magnifiedpathology image. For example, the time a pathologist is looking at aregion can be used as a proxy for confidence and/or an indication thatthe region is of more interest.

In one embodiment, digital camera 103 outputs a video including themagnified pathology images, and processing apparatus 109 furtherincludes logic that causes processing apparatus 109 to stitch togetherframes in the video to form a plurality of high-resolution images. Thiscan be used to create comprehensive magnified pathology images of onlythe relevant portions of a sample at various levels of magnification(see infra FIG. 3). Moreover, forming the image database does notinterrupt the pathologists workflow since, in this embodiment, only theportions of the sample the pathologist looks at are used to stitchtogether the high-resolution images. Videos and vocal annotations may berecorded simultaneously, or they can be time-stamped and recordedseparately, to be combined later.

FIG. 2 illustrates a pathology database 201, in accordance with anembodiment of the disclosure. Pathology database 201 may be createdusing system 100 of FIG. 1, and may be stored on storage 121 (e.g., harddrives, solid state drives, etc.). As shown in the depicted embodiment,pathology database 201 includes pathology images (e.g., video frames)that were captured by a digital camera (e.g., digital camera 103). Thepathology images are indexed with respect to their frame number,recording time, the voice annotation of the pathologist (transcribed),microscope stage position, magnification they were collected at, andlocation of pathologist gaze. One skilled in the art will appreciatethat the system depicted in FIG. 1 can be used to create a database withany number of dimensions and inputs and is not restricted to thosedimensions/inputs depicted here.

As illustrated a digital camera (e.g., digital camera 103) opticallycoupled to a microscope (e.g., microscope 101) may start recordingimages of pathology samples as a digital video or still frames. Eachframe of the video is indexed with respect to its capture time. Forexample in the depicted embodiment, frame one was captured during thefirst three microseconds of recording, frame two was captured in thefourth through seventh microseconds of recording, etc. A microphone(e.g., microphone 105) may also record the voice annotation of a user ofthe microscope. The vocal annotations may be converted into text and/orindexed to their respective recording time and video frame. In thedepicted embodiment, while frame one was captured (during the firstthree microseconds of recording) the pathologist said the word “this”;in subsequent frames the pathologist stated “looks like lymphatic tissueand may be benign.” In one embodiment, other metadata about the patientalong with geographical information (which might later unveil anoutbreak of a virus in a specific geographic area for example) may alsobe collected and included in the pathology database.

The system may also record the position of the microscope stage andindex it with respect to the recording time and the magnified pathologyimages. In the depicted embodiment, the location of the stage ismeasured with X, Y coordinates from a (0,0) point which is the lowerleft hand position of the stage, and the stage movement is measured inmicrons. However, in other embodiments the stage axis may be orienteddifferently (e.g., the (0,0) point is located at the bottom right handposition of the stage), the units of measurement may be different (e.g.,mm, cm, etc.), and the Z position of the stage may also be recorded.Furthermore, “stage position” should be broadly construed because it isused to identify specific locations on samples, which one skilled in theart will appreciate may be achieved in any number of ways. In oneembodiment, stage position is determined optically with respect to thedimensions of the slide being imaged, and not with respect to themicroscope hardware. As shown, the magnification that a specific framewas viewed with is also recorded with respect to recording time,transcribed text, stage position, and gaze quadrant.

The user's gaze may also be indexed with respect to the otherdimensions/inputs illustrated and discussed. In the depicted embodiment,the gaze of the user/pathologist is measured in quadrants; meaning theimage the user sees is subdivided into four sub-images, and the systemrecords which sub-image the user was looking at during the recordingtime. This may be achieved with hardware/software installed in themicroscope, or other external systems, as one skilled in the art willappreciate that there are many different ways to detect gaze. Moreover,while the embodiment depicted here only illustrates very generally wherethe pathologist/microscope user was looking, in other embodiments theexact coordinates that the user was looking at are recorded.

In one embodiment, indexing the magnified pathology images and the voiceannotation may include tagging the voice annotation of the user to aregion of interest in the magnified pathology images. For instance, inthe embodiment depicted above, the pathologist's diagnosis of “benign”is associated with stage position coordinates (136, 47) at 40×magnification, and he/she was looking in quadrants 3 and 4. This allowsa person reviewing the pathologist's work to know exactly where thepathologist was looking when the determination of “benign” was made.Further the person reviewing the pathologist's work knows the history ofexamination (how much of the slide had been examined up to that point).In the depicted embodiment, the processing apparatus may further includelogic that when executed by the processing apparatus causes theprocessing apparatus to convert the pathologist's voice annotation totext, and the text is indexed with respect to recording time and themagnified pathology images, among the other dimensions/inputs mentionedand discussed. In another or the same embodiment, the pathologist may beable to review the pathology images collected and directly annotate theimage to show a region of interest (e.g., circle the cancer cells on thedigital image, place a star next to an unknown cell formation, etc.).

Lastly, it is worth noting that more than one pathologist may look atand annotate a pathology sample. Additional database rows and/or columnsmay be added so that information from both pathologists is captured.Both of the pathologists' input can then be compared to generate aground truth/augment regarding what is known about the sample/slide.Redundancy of information about a pathology sample may make thediagnosis in the pathology database more robust.

FIG. 3 illustrates image entries in the pathology database of FIG. 2, inaccordance with an embodiment of the disclosure. In the depictedembodiment, several magnifications of the same pathology sample areshown. In this embodiment, a pathologist used an imaging system (e.g.,system 100 of FIG. 1) to look at several portions of a pathology sampleunder different levels of magnification. It is important to note thatthe pathologist did not look at the whole sample under allmagnifications. For instance under 20× the whole sample may be visible;however, because only a small portion of the sample is relevant formaking a diagnosis, the pathologist only bothered to zoom in on the oneportion of the sample. Accordingly, the pathologist zoomed in to viewthat portion under 40× magnification. The pathologist then furtherzoomed in on two separate spots contained in the 40× portion of theimage, and viewed these under 60× magnification. It is possible thatthese small sections of the pathology sample are the only portionsgermane to diagnosis. Since a camera was capturing all of the action bythe pathologist, the camera has captured incomplete pictures of thesample under 40× and 60× magnification. However, this does not impactthe ability of someone reviewing the pathologist's work to understandwhy the diagnosis was made, since the person reviewing the work can seethe portions of the sample relevant to diagnosis (and hear a recording,or view transcribed text, of the pathologist's vocal annotations).

Further in one embodiment, to make the holes in the different levels ofmagnification more visually appealing, the processing apparatus maygenerate image data for the un-imaged holes. This allows a reviewer ofthe captured images to fluidly move between the imaged portions of thesample without visual discontinuity from the un-imaged portions. In thisembodiment, the generated image data may be clearly identified as notactual image data (e.g., the generated image data may be outlined withred lines, appear in grayscale, appear partially transparent, or containoverlaid words like “generated data”, etc.). In one embodiment, amachine learning algorithm is used to generate the image data.

FIG. 4 is a flow chart illustrating a method 400 of pathology datacapture, in accordance with several embodiments of the disclosure. Theorder in which some or all of process blocks 401-411 appear in method400 should not be deemed limiting. Rather, one of ordinary skill in theart having the benefit of the present disclosure will understand thatsome of method 400 may be executed in a variety of orders notillustrated, or even in parallel.

Block 401 illustrates magnifying a pathology sample with a microscope toform magnified pathology images. As discussed above, a pathologist mayexamine pathology samples through a conventional microscope, or may lookat pathology samples with a custom microscope that is specially adaptedto the systems described here (e.g., system 100 of FIG. 1 with alldepicted components embedded in microscope 101).

Block 403 shows recording the magnified pathology images with a digitalcamera optically coupled to the microscope. The microscope discussed mayinclude a digital camera that is constantly recording video or stillframes of the portions of the sample that the pathologist is viewing. Inone embodiment, the processing apparatus stitches together frames in thevideo to form a plurality of high-resolution images (see supra FIG. 2)

Block 405 depicts recording voice annotation from a user of themicroscope with a microphone. While the pathologist is viewing themagnified pathology images, the pathologist may be simultaneouslyvocally annotating what he/she sees. For example the pathologist maylook at particular portion of the magnified pathology image and statehis/her general impression about the image. For example the pathologistmay say something to the effect of “while the cells in this portion ofthe sample are a little atypical, there doesn't seem to be any melanoma”and the microphone may record this speech. However, sometimes recordingvoice annotation may be asynchronous: the pathologist doesn't commentwhile viewing, but when done examining the slide, he/she dictates thewhole report.

Block 407 shows transferring the magnified pathology images and thevoice annotation to a processing apparatus electrically coupled to thedigital camera and the microphone. Transferring the magnified pathologyimages and the voice annotation may occur in real time (i.e., as themicrophone and the camera are capturing image data and sound data) ormay occur after the pathologist finishes the whole recording. Oneskilled in the art will appreciate that there are many different ways tofacilitate transfer of both images and sound data, and that any one ofthese techniques may be used in accordance with the teachings of thepresent disclosure.

Block 409 illustrates using the processing apparatus to performsoperations including recording the magnified pathology images and thevoice annotation to a storage medium. The storage medium may be RAM,ROM, flash memory, hard disk, or the like. The processing apparatus maystore the information locally (e.g., on a hard drive contained in, orwired/wirelessly connected to, the processing apparatus) or may uploadthis information to a remote sever, distinct from the processingapparatus, via the internet or local area network. In one embodiment,the processing apparatus forms a database with both the magnifiedpathology images and the voice annotation. Further, the processingapparatus may convert the speech to text using any natural languageprocessing technique; the text may be indexed with respect to therecording time and the magnified pathology images.

Block 411 depicts using the processing apparatus to performs operationsincluding indexing the magnified pathology images and the voiceannotation with respect to recording time. In one embodiment, indexingthe magnified pathology images and the voice annotation includes taggingthe voice annotation of the user to a specific location in the magnifiedpathology images. Thus anyone reviewing the pathologist's work canclearly see/hear the rationale behind the diagnosis.

In one embodiment, the position of the microscope stage is recorded toprovide information about the location of where the pathologist waslooking. Again, this may be useful to determine why a pathologist made aparticular diagnosis. Stage position may be determined optically with ascale bar on the sample or the like. Magnification level may alsoprovide useful position information. The magnification level of themicroscope may be transferred to the processing apparatus, and theprocessing apparatus indexes the magnification level with respect to therecording time, the magnified pathology images, and the position of themicroscope stage. This optical information may be used independentlyfrom, or in conjunction with, the physical position of the microscopestage to determine the location of an image relative to the pathologysample.

In one embodiment, the motion data of the stage could be used to informthe camera to turn on. For example, when the stage is stationary thecamera will not capture videos, but will capture images (single frames).Conversely, when the stage is moving the camera may collect video. TheX, Y, and Z vectors of movement may be treated separately (for example,video would be captured when the stage is moving in the X, Y directions,but not when the stage is moving in the Z direction).

In one embodiment, the processing apparatus may be configured to removeimage artifacts from the magnified pathology images. If the motion ofthe stage (X, Y, Z) has been recorded, the computed motion can becompared to the recorded motion, and the difference can be used toassess the quality of the video data: if both are in agreement, thevideo data is highly reliable. But in the case of a strong discrepancy,the video data contains artifacts, and the corresponding frames can betagged and not used for further processing, mosaicking, etc.

In one embodiment the processing apparatus further tracks the gaze ofthe user to determine a region of interest, and the region of interestis indexed with respect to recording time, the magnification setting,and magnified pathology images. This allows someone reviewing the workof the pathologist to clearly identify the important portions of themagnified pathology images.

The processes explained above are described in terms of computersoftware and hardware. The techniques described may constitutemachine-executable instructions embodied within a tangible ornon-transitory machine (e.g., computer) readable storage medium, thatwhen executed by a machine will cause the machine to perform theoperations described. Additionally, the processes may be embodied withinhardware, such as an application specific integrated circuit (“ASIC”) orotherwise.

A tangible non-transitory machine-readable storage medium includes anymechanism that provides (i.e., stores) information in a form accessibleby a machine (e.g., a computer, network device, personal digitalassistant, manufacturing tool, any device with a set of one or moreprocessors, etc.). For example, a machine-readable storage mediumincludes recordable/non-recordable media (e.g., read only memory (ROM),random access memory (RAM), magnetic disk storage media, optical storagemedia, flash memory devices, etc.).

The above description of illustrated embodiments of the invention,including what is described in the Abstract, is not intended to beexhaustive or to limit the invention to the precise forms disclosed.While specific embodiments of, and examples for, the invention aredescribed herein for illustrative purposes, various modifications arepossible within the scope of the invention, as those skilled in therelevant art will recognize.

These modifications can be made to the invention in light of the abovedetailed description. The terms used in the following claims should notbe construed to limit the invention to the specific embodimentsdisclosed in the specification. Rather, the scope of the invention is tobe determined entirely by the following claims, which are to beconstrued in accordance with established doctrines of claiminterpretation.

What is claimed is:
 1. A method for pathology data capture, comprising:magnifying a pathology sample with a microscope to form magnifiedpathology images; recording the magnified pathology images with adigital camera optically coupled to the microscope; transferring themagnified pathology images to a processing apparatus electricallycoupled to the digital camera, wherein the processing apparatus performsoperations including: stitching together the magnified pathology imagesto form a plurality of high-resolution images, wherein the plurality ofhigh-resolution images include un-imaged holes; and generating imagedata that is not actual image data for the un-imaged holes, wherein theun-imaged holes are disposed between individual magnified pathologyimages used to form the plurality of high-resolution images.
 2. Themethod of claim 1, further comprising identifying, with the processingapparatus, that the generated image data for the un-imaged holes is notactual image data.
 3. The method of claim 2, wherein identifyingincludes at least one of outlining the generated image data, changingthe color of the generated image data, changing the transparency of thegenerated image data, or labeling the generated image data.
 4. Themethod of claim 1, wherein generating the image data includes using amachine learning algorithm to generate the image data.
 5. The method ofclaim 1, further comprising storing the magnified pathology images in adatabase.
 6. The method of claim 5, further comprising: tracking a gazeof the user to determine a region of interest; storing the region ofinterest in the database, wherein the region of interest is indexed withrespect to recording time and the magnified pathology images.
 7. Themethod of claim 5, further comprising: recording a position of amicroscope stage of the microscope; and storing a position of themicroscope stage in the database, wherein the position of the microscopestage is indexed with respect to recording time and the magnifiedpathology images.
 8. The method of claim 5, further comprising:recording voice annotations with a microphone coupled to the processingapparatus; and storing the voice annotations in the database, whereinthe voice annotations are indexed with respect to recording time and themagnified pathology images.
 9. The method of claim 8, further comprisingconverting the voice annotations to text using the processing apparatus,wherein the text is indexed with respect to the recording time and themagnified pathology images.
 10. The method of claim 9, wherein theprocessing apparatus includes a distributed system.
 11. At least onemachine-accessible storage medium that provides instructions that, whenexecuted by a machine, will cause the machine to perform operationscomprising: receiving magnified pathology images; stitching together themagnified pathology images to form a plurality of high-resolutionimages, wherein the plurality of high-resolution images includeun-imaged holes; and generating image data that is not actual image datafor the un-imaged holes, wherein the un-imaged holes are disposedbetween individual magnified pathology images used to form the pluralityof high-resolution images.
 12. The at least one machine-accessiblestorage medium of claim 11, further providing instructions that, whenexecuted by the machine, will cause the machine to perform furtheroperations, comprising: identifying that the generated image data forthe un-imaged holes is not actual image data.
 13. The at least onemachine-accessible storage medium of claim 12, wherein identifyingincludes at least one of outlining the generated image data, changingthe color of the generated image data, changing the transparency of thegenerated image data, or labeling the generated image data.
 14. The atleast one machine-accessible storage medium of claim 11, whereingenerating the image data includes using a machine learning algorithm togenerate the image data.
 15. The at least one machine-accessible storagemedium of claim 11, wherein receiving the magnified pathology imagesincludes receiving the magnified pathology images with a database. 16.The at least one machine-accessible storage medium of claim 11, furtherproviding instructions that, when executed by the machine, will causethe machine to perform further operations, comprising: receiving aposition of a microscope stage; and storing a position of the microscopestage in the database, wherein the position of the microscope stage isindexed with respect to recording time and the magnified pathologyimages.
 17. The at least one machine-accessible storage medium of claim15, further providing instructions that, when executed by the machine,will cause the machine to perform further operations, comprising:receiving voice annotations with the database; and indexing themagnified pathology images and the voice annotations with respect torecording time and the magnified pathology images.
 18. The at least onemachine-accessible storage medium of claim 17, further providinginstructions that, when executed by the machine, will cause the machineto perform further operations, comprising: converting the voiceannotations to text, wherein the text is indexed with respect to therecording time and the magnified pathology images.
 19. The at least onemachine-accessible storage medium of claim 18, wherein the voiceannotations are converted to text using natural language processing. 20.The at least one machine-accessible storage medium of claim 18, whereinthe machine includes a distributed system.